Influence of weather conditions on children’s school travel mode and physical activity in 3 diverse regions of Canada
Bibliographic record
Abstract
Children who engage in active school transportation (AST) have higher levels of physical activity (PA). Climate and weather were shown to influence adults’ daily travel behaviours, but their influence on children’s AST and PA has been less examined. This study examined the influence of weather conditions on children’s AST and overall PA. Children in grades 4 to 6 (N = 1699; age, 10.2 ± 1.0 years) were recruited in schools located in urban, suburban and rural areas, stratified by area-level socioeconomic status, in 3 different regions of Canada (Trois-Rivières, Québec; Ottawa, Ontario; Vancouver, British Columbia). Mode of school travel was self-reported and physical activity was measured using a pedometer. We used publicly available data on total precipitation and early morning temperature. AST increased with temperature only among girls. Daily precipitation was negatively associated with boys’ and girls’ PA while warmer temperature was associated with increased PA on weekend days. We also observed that season and region moderated the relationship between weather conditions and children’s physical activity behaviours. Our results suggest that daily weather variations influence children’s AST and PA to a greater extent than seasonal variations. Interventions designed to help children and families adapt to weather-related barriers to AST and PA are needed. Novelty: In Canada, weather conditions may influence children’s active behaviours daily. Associations between weather conditions, choice of travel mode and physical activity vary by sex, season, and region. Weather affects children's PA differently during the week than on weekends.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".